Networks and Vehicles Follow Similar Journey to Automation

Autonomous vehicles (let’s call them AVs) and Autonomous Networks (ANs) are road-mates; they’ve essentially traveled the same route in the quest for full automation. They share the overarching Holy Grail objective of zero-touch operation, undisturbed by human hand as they go about the full range of their respective operations.

The Society of Automotive Engineers (SAE) has defined a six-degree taxonomy that classifies the level and type of automation capabilities in a given vehicle. This is summarized on Wikipedia’s Self-Driving Car page and illustrated in Figure 1.

Figure 1: SAE levels of vehicle automation

Both AVs and ANs have already arrived at their third level of automation, i.e. partial automation, where most of what they do is automated—but human supervision, monitoring, and even interaction is still needed. And just as AVs have relied upon an evolving set of building blocks over decades, ANs have also employed and built upon a number of tools along the way. Figure 2 illustrates this cumulative evolution.

Figure 2: Building blocks of network evolution

There are many examples of these building blocks in the network world. For instance, we have the availability and growing adoption of zero-touch provisioning (ZTP); YANG model-based open interfaces (NETCONF, REST APIs, gNMI/gNOI); gRPC-based deep-streaming telemetry; extensive, detailed logging and monitoring; and streaming for rapid fault isolation and prediction.

Perhaps the most critical characteristic that AVs and ANs share is that in order for their potential to be fulfilled, diverse stakeholders need to come together and coordinate. In the AV world, massive efforts are underway at every level (governments, cities and towns, car companies, insurance companies, and technology vendors) to standardize and streamline end-to-end operations based on key principles of interoperation, openness and reliability.

For ANs, there is a similar and pressing need by networking community for collaborative, coordinated development of an open, generic framework for a fully autonomous optical network, which could be used for setting up reference use cases that can be extended to various network architectures. This framework should be driven by the primary requirement of ZERO human intervention in network operations after initial deployment—including configuration, monitoring, fault isolation, and fault resolution. The framework should leverage currently available tools and technologies for full-featured and automation-ready software, such as Fujitsu System Software version 2 (FSS2) for network element management, in conjunction with Fujitsu Virtuora®, an open network control solution for network element and network management.

Efforts to achieve autonomous networks and autonomous vehicles show strong similarities in terms of both pace and trends.  These similarities are driven by common objectives to, primarily, address scale and the need for a growing number of applications, while tackling the human error element, and enabled by an intertwined and cross-dependent set of technology advancements and adaptations.

About Muhammad Sarwar

Working as a key contributor to Fujitsu’s network solutions strategy, architecture and portfolio, Muhammad Sarwar applies his extensive expertise in multiple areas. These include future product and roadmap planning; product and partnership management; idea and product incubation; and innovation in digital transformation. His particular areas of interest include data center networking; network management, abstraction, and security; automation and analytics; SDN/NFV; and emerging technologies in areas such as augmented reality, autonomous/connected vehicles, and blockchain.